Whether you’re a business owner or marketing expert, you understand the importance of knowing your audience inside and out is key to attracting prospects and retaining existing customers. Fortunately, there are a number of tools on the market that can help you do just that.

Through cloud call center software available from companies like Aspect, you’re able to get a more complete picture and understanding of your customers, from their search behavior and purchase patterns to their history of interactions with your company.

Here are several ways this tool can help you achieve that highly-desired, 360-degree view of your customers.

Personalization

Aspect’s cloud call center allows for businesses to get a more personalized look at each and every customer. In particular, the software can provide insights into customers’ purchase and spending history, as well as the frequency with which they do business with your company. Indeed, gaining these insights will allow you to retarget specific customers — based on their specific desires — with similar products or must-have accessories, which will keep them coming back time and time again.

Furthermore, call center software in the cloud gives you the ability to recall every customer’s recent interaction history with your company. For example, when a specific customer calls your support line more than once, your live agents will already have a number of tools at their fingertips — this may include who the customer initially spoke with and the details of their previous conversations — to more seamlessly resolve any outstanding issues.

Convenience

Another great customer-focused aspect of cloud call center software is its omnichannel capabilities. Of course, not all customers prefer the same methods of communication. But by providing omnichannel options, customers can reach your live agents through a number of different mediums, including voice, email, text messaging, live chat and social media.

For example, if a customer prefers to be contacted via text and requests a status update on their most recent purchase, your live agents can text them in real time with the requested information, allowing the customer to respond when it’s most convenient for them.

But perhaps one reason why employing omnichannel options can be valuable to your company is the ability for customers to reach support agents 24/7. No matter the time of day, employing a cloud contact center gives you the ability to offer live chat support via your website, where customers can ask questions at any time from virtually anywhere.

Ultimately, this allows your company to fit the individual needs of a variety of different customers around the clock, even outside of normal business hours.

Satisfaction

Last but not least, cloud call center software allows your company to track customer satisfaction scores by deploying surveys to gather important feedback. Simply tailor your questions to your liking and specific needs in order to gain crucial customer insights and gauge which areas of your business need some fine-tuning.

Cloud call center software can help you achieve this through both stand-alone and post-call surveys that can be deployed after a voice call or via text message. For example, you can deploy a post-call survey to use for training purposes or to simply gain additional feedback from your customers.

You can also deploy an in-app survey to gauge user experience, mobile-friendliness and overall satisfaction with your company. Gaining these types of insights are valuable, as the feedback comes directly from the customer, which can then help you make the best business decisions with their interests in mind.

Capturing a More Complete Picture

By using cloud call center software to aggregate customer data, your company will be able to gather a more complete picture of each and every customer. In the end, better understanding your customers’ desires will help your company in future retargeting strategies and, in turn, help retain this clientele.

Customer relationship management software has emerged as one of the most crucial tools for doing business successfully today, and the power of big data predictive analytics is making CRM more powerful than ever. The CRM predictive analytics market, valued at $4.18 billion in 2014, is expanding at a compound annual growth rate of 12.83 percent, on track to be worth $7.65 billion by 2019, Markets and Markets projects. CRM analytics tools are in demand because they help companies predict market behavior, understand their buyers and make more sales.

Companies that know how to use CRM predictive analytics effectively have a major marketing and sales advantage over rivals who aren’t taking advantage of this revolutionary technology. Here’s a look at three ways CRM predictive analytics can help you gain an edge over your competition and take the lead in your market.

Predicting Customer Demand Surges

CRM lets you make predictions about future marketing and sales trends based on historic data. One important application of this is predicting what your customers will want and when they will want it. This can help you ensure that the products and services you’re selling are what your customer base wants and that you’ll have your inventory and staff prepared to meet peak demand times.

One of the most valuable uses of this approach is predicting holiday sales trends. For instance, most retailers center their annual sales around certain key sales days such as Black Friday, but a review of the actual data shows that seasonal sales peaks over the Christmas shopping season can last anywhere from 38 to 88 days depending on the market sector, explains Marketing Week writer Mindi Chahal. Knowing when your holiday sales peak begins and when it ends can make you better prepared to have sufficient staff on hand and sufficient items in stock to meet the surge in demand.

Understanding Your Target Market

Another valuable application of predictive CRM analytics is helping you narrow your target market. Traditional market research methods are effective as far as they go, but the amount of data they can manage is limited. Big data analytics can provide a more complete analysis of your market by integrating data from many sources, including customer purchase history, social media profiles and emails. This enables you to spot characteristics of your target market that you might otherwise overlook.

A good illustration of how this can be applied effectively is the type of recommendation engine used by companies such as Amazon and Netflix. By analyzing buyer behavior and demographic characteristics, these companies generate repeat business by making recommendations designed to appeal to customers’ buyer profiles.

Helping Your Staff to Make Data-based Sales Decisions

Just as recommendation engines can help your website optimize automated sales efforts to online buyers, CRM predictive analytics can also help your sales team make data-driven sales decisions when interacting with prospective buyers. Your sales managers can see who your hottest prospects are, as well as which of your top sales representatives are available for deployment. Your sales representatives can see data about customers’ purchase history, demographic characteristics and buying preferences, enabling them to make more effective sales presentations.

In order to use CRM tools effectively for these types of applications, your staff will need specialized training. Customer FX provides Infor CRM training to help companies make the most of CRM tools. Scheduling this type of training can empower your marketing and sales teams to put CRM predictive analytics tools to optimal use in order to boost your sales performance, grow your profits and gain an edge on your competition.

About the Author

Roy Rasmussen, coauthor of Publishing for Publicity, is a freelance writer who helps select clients write quality content to reach business and technology audiences. His clients have included Fortune 500 companies and bestselling authors. His most recent projects include books on cloud computing, small business management, sales, business coaching, social media marketing, and career planning.

Wondering whether you should invest in AI and Machine Learning? That’s a question that the most innovative companies are considering. Why consider it? One good reason is because your competitors have already started. If that doesn’t give you some reason to get motivated, I hope you get started before you are put out of business. To make sure that doesn’t happen, there are a few things to consider to help you start to explore an investment in machine learning.

It’s the Data, Stupid

Of course, as with any business initiative, you’ll want to create value. And this can be done using machine learning systems. But for those systems to provide value, companies will need to begin by evaluating their organization’s data maturity, but more importantly their readiness to accomplish its data-driven goals. Company’s need to start with an audit of their data warehousing, data scientific research capabilities, data governance and data hygiene. In addition, it’s important to look at the sources, uses, volume, and veracity of all your date, meaning your first-, second-, and third-party data.

Garbage in, Garbage Out

Why is making sure your data so clean? Machine learning is basically taking a computer and making it smart enough to learn from the data it’s fed. We are essentially programming machines to learn. The goal is that after a certain point of time, the computer is able to predict further data. How so? Let’s pretend you want to make your computer predict the weather. So to begin, you might feed the computer weather reports of every hour of every over the past year. What you might end up with is– because the temperature (z) depends on day of the year (x) as well as the time of the day (y), more than two-dimensional curve. In fact, weather is random, so the equation generated by the computer won’t just have 3 variables (x, y, z), it may also have higher powers. So depending on the number of factors in a prediction and the randomness of the outcome, the complexity of the curve can increasingly get more complicated.

So back to the data… And I know you know the story about data: garbage in, garbage out. So hopefully, now you see can why good, clean data is so important to prediction. As the computer is taking the data you feed it to make future predictions, those predictions dependent on the data you are feeding it. So you want the very best data possible. And it takes super computers which are capable of handling large volumes of data, as well as the ability to learn fast and to make fast decisions based on the learning it under goes.

AI and ML Are Not The Same

Often times Artificial Intelligence (AI) and Machine Learning (ML) are used interchangeably. But they are actually different. Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart.” Machine Learning is the application of AI based on the idea that we should be able to give machines access to data and let them learn for themselves. Artificial Intelligence devices (devices designed to act intelligently), are often classified into one of two groups: 1) applied and 2) general.

Applied AI is far more common. Applied AI is about systems designed to intelligently trade stocks and shares or drive an autonomous vehicle. Generalized AI is may up of systems or devices that, in theory, can handle any task. And are less common. However, this is where some of the most exciting advancements are happening today.

Deep Learning is A New Area of Machine Learning Research

It was introduced with the objective of moving Machine Learning closer to one of its original goals: that of being Artificial Intelligence. So essentially Deep Learning is a subfield of machine learningconcerned with the algorithms inspired by the structure and function of the brain called artificial neural networks. Deep learning has worked it’s way into business language via Artificial Intelligence (AI), Big Data and analytics. Deep learning is an approach to AI which shows great promise when it comes to developing the autonomous, self-teaching systems which are revolutionizing many industries.

The Two Big Ideas: It May Be Possible To Teach Computers to Learn and The Internet is a Source of a Ton of Data

Arthur Samuel, in 1959 is credited as the one who came up with the big idea that it might be possible to teach computers to learn for themselves. That would be in contrast to teaching computers everything they need to know about the world and how to carry out tasks. The second big idea was that the Internet, with huge increase in the amount of digital information being generated, stored and could be used for analysis. So the scientists and engineers realized it would be far more efficient to code computers to think like human beings, and then plug them into the internet to give them access to all of the information in the world.

Neural Networks Are Algorithms

Neural networks are a set of algorithms, modeled loosely after the human brain and designed to recognize patterns. The development of neural networks has been key to teaching computers to think and understand the world in the way we do, in addition to the innate advantages they hold over people such as speed, accuracy and lack of bias. So a Neural Network is a computer system that classifies information in the same way a human brain does. It can be taught to recognize, for example, images, and classify them according to elements they contain. It works on a system of probability – which means that based on data it’s fed, it is able to make statements, decisions or predictions with a degree of certainty. The addition of a feedback loop enables “learning” – by sensing or being told whether its decisions are right or wrong and then can modify the approach it takes in the future.

What Can Machine Learning Applications Do?

Machine Learning applications can read text and work out whether the person who wrote it is making a complaint or offering congratulations. They can also listen to a piece of music, decide whether it is likely to make someone happy or sad, and find other pieces of music to match the mood. They can even compose their own music expressing the same themes, or which they know is likely to be appreciated by the admirers of the original piece.

These are all possibilities offered by systems based around ML and neural networks. The idea is that we should be able to communicate and interact with electronic devices and digital information, as naturally as we would with another human being. And another field of AI – Natural Language Processing (NLP) – has become an exciting area of innovation in recent years, and one which is heavily reliant on machine learning. (And yes, my initials just happen to be NLP, but that doesn’t really mean anything… just a happy coincidence…)

Where is Used?

Take Google for instance. Google is using it in its voice and image recognition algorithms. It is also used by Netflix and Amazon to decide what you want to watch or buy next. And it is also being by researchers at MIT to predict the future. While Machine Learning is often described as a sub-discipline of AI, we might look at Machine Learning as the state-of-the-art of AI. Why? Perhaps because it is showing the greatest promise to provide tools that industry and society can use to drive change.

More on the practical uses of AI and ML in the future. For now, noodle on that!

Digital business is increasing the potential monetary value of data, but most companies aren’t leveraging this valuable resource. Smart devices, mobile technology and social media are increasing the volume and variety of customer data available at an accelerated rate, turning data brokering into a multibillion dollar business while simultaneously making data more affordable than ever. General information about consumers is now available for about $0.50 per 1,000 people, estimates the Financial Times. Read on for the trends that are transforming data collection and the tools that smart companies are using to turn data into profit.

Internet of Things

One of the biggest technology trends is the increasing presence of smart electronic devices, a trend known as the Internet of Things (IoT). Earlier stages of the Internet were centered around personal computers and then mobile phones, and now the Internet of Things includes all sorts of smart devices, from smart houses to smart TVs to smart cars, watches and clothes.

All these devices collect data that is centered around the consumers who use these devices. This enables businesses to organize their market research and advertising efforts around the totality of data as well as individual uses, a trend known as marketing personalization. The Internet of Things means that the data collected can conceivably be used to personalize ads they see in their car, at work and while shopping.

Location-Based Data

The Internet of Things forms a digital mesh that enables consumers and their data to be pinpointed by location. Smartphones like the Samsung Galaxy Note5 are GPS-enabled, allowing marketers to collect data on their location and deliver personalized messages that appeal to customers at specific locations.

One of the emerging applications of this is beacon marketing, which identifies when customers are entering stores to deliver customized coupons, discounts and other special offers. For instance, Hillshire Brands saw a 36 percent increase in brand awareness and a 20 percent increase in purchase intent by using beacon technology.

Context-Sensitive Data

Data collection is becoming more context-sensitive. For instance, a webpage that displays well on a desktop screen needs to adjust to be viewable on a smaller mobile device screen. This means that the site needs to collect context-sensitive data about the viewer’s device and screen size.

Another context-sensitive use of data is retargeted advertising, when information gathered on one device follows users as they use other devices. For instance, Yahoo recently added a feature to its Gemini ad marketplace that enables advertisers to send retargeted ads to customers on websites, apps and Yahoo interest categories based on their browsing behavior.

Social sites are seeking to capitalize on this, with Facebook, Twitter, Instagram, Pinterest, Google and YouTube all introducing buy button features last year. In 2016, social media brand engagement and buying will drive data collection, predicts Brandwatch.

About the Author

Roy Rasmussen, coauthor of Publishing for Publicity, is a freelance copywriter who helps small businesses get more customers and make more sales. His specialty is helping experts reach their target market with a focused sales message. His most recent projects include books on cloud computing, small business management, sales, business coaching, social media marketing, and career planning.

New Call Tracking For Digital Marketing – Well if you thought the only people who cared about phone calls to brand were people in the contact center, then you may be surprised by DialogTech’s new solution. Actually its not that surprising me – considering a good 30-50% of calls to a contact center are marketing related – like which size would be better for me, or what are the measurements of the “box” or is the delivery date different than the ship date. These are all questions that would lead someone to “buy” something or not. However, often times those “marketing” type calls go to the contact center. The contact center rarely gets credit for answering lead conversion calls, but many of them do it all the time. Now to the announcement…

DialogTech, who provides of a most comprehensive, end-to-end call attribution and conversion platform for data-driven marketers, announced a breakthrough in call tracking for digital marketing with the release of SourceTrak 3.0. Nearly two years in the making, SourceTrak 3.0 enables the world’s largest organizations to realize the full benefits of call tracking for digital marketing, without the traditional limitations.

What is Included In This New Call Tracking for Digital Marketing?

According to eMarketer, 62.6 percent of digital ad spending in the U.S. this year will target smartphones and mobile devices. As a result, these ads will drive 162 billion calls to businesses by 2019, according to analyst firm BIA/Kelsey. So what is important is to know which programs generate the most calls (and customers) – because its a necessary step to measure and optimize digital marketing performance.

DialogTech’s newly re-architected and enhanced SourceTrak 3.0 technology solution is designed to meet the data, affordability, reliability and ease-of-implementation requirements of Fortune 1000 companies, large multi-location organizations and the marketing agencies they work with.

Enterprise marketing teams and agencies already analyze and optimize the customer journey for the search keywords, digital ads and website interactions that generate online engagement. DialogTech’s SourceTrak 3.0 enables them to do the same for offline phone call conversions. The call data appears alongside the online data in the marketing solutions they already use and requires no change to current processes and causes no disruption to digital ads or website performance.

What is Included In This New Call Tracking for Digital Marketing?

Full Attribution For Every Phone Number on a Website – Provides complete call attribution data – including the search keywords, digital ads, referring websites and webpages that drove the call – for every call from every phone number displayed on a website, including every number shown in “Find a Dealer” and “Find an Agent” webpages consumers use to locate and call their closest location or agent.

Keyword Attribution for Every Call From Google AdWords – Whether a call comes from a “Call” button in a Google search ad or from a searcher who clicks through to a website, SourceTrak 3.0 captures complete keyword, session and caller data for every call. That call attribution data, as well as any revenue generated from the call, can be imported directly into Google AdWords alongside online data for a complete and accurate analysis of search advertising ROI.

Fast, Seamless Implementation – SourceTrak 3.0 enables marketing teams and agencies to implement call tracking on any website in a few clicks without any help from IT, any negative impact on website performance or SEO ranking or any disruption to existing digital ads.

SourceTrak 3.0 technology is available as part of the DialogTech Voice360® platform, which also includes an integrated suite of marketing solutions for caller qualification and scoring, contextual call routing and management, conversation analytics and spam call blocking. All SourceTrak 3.0 features are backwards compatible with SourceTrak 2.0, and all SourceTrak 2.0 users have automatic access to the new functionality.

For more information on how to get started today, contact DialogTech at DialogTech.com.

If you are part of a contact center, how many of your calls are marketing oriented vs “help me fix this” type calls? Should Marketing pay for some of the contact center costs if a percentage of the calls are lead conversion related? These are the questions we will be asking ourselves as we see Marketing, Sales and Customer Service converge into commerce.

What is Audience Studio? NBCUniversal wants to make it easier for advertisers to use data to target audiences more precisely across TV, digital and social media. The media company, owned by Comcast Corp. , is introducing a new division called Audience Studio, which is dedicated to helping marketers employ data for ad targeting purposes by tying together four different ad buying products NBCU has introduced over the past few years. Audience Studio is being led by Denise Colella, NBCU’s senior vice president of data platforms and strategy who is in the midst of putting together a team of specialists for the new endeavor, including several planned hires.

Does Audience Studio Have a Data Management Platform? In addition to the group of ad targeting experts, at the heart of Audience Studio is a new “data management platform.” It’s basically a set of digital tools that advertisers will be able to use to match their own data with data from NBCU and third-party sources, in order to put together ad targeting segments, such as new moms in the market for a family friendly car. Marketers can then use that information to direct their advertising to those groups on TV and the Web.

What Four Offerings Does Audience Studio Include? Audience Studio will essentially tie together four recently launched NBCU ad offerings: Its Audience Targeting Platform lets advertisers target specific audiences on linear TV, and NBCUx is a similar product for digital media. NBCU+ Powered by Comcast provides marketers some access to Comcast set-top data for ad targeting purposes. And Social Synch helps brands extend the reach of their ad buys across various social networks.

Why Is Audience Studio An Interesting Opportunity for Marketers? Until now, a marketer looking to take advantage of two or more of these tools might have had to input data several different ways and come up with different definitions of potential ad targeting segments. Brands were largely then left to try to match up the segments manually. As more advertisers look to employ data-centric ad strategies across multiple media outlets, the process has the potential to cause major headaches, according to Krishan Bhatia, executive vice president of business operations and strategy at NBCU.

“If before you had this Chinese Wall between groups, with this, you are permeating that,” Mr. Bhatia said. “Going forward, a brand can now align their data inputs and outputs.”

What’s the Most Difficult Part of Targeting the Right Audience Segments? Naturally, advertisers want to eliminate any potential barriers when trying to increase their use of sophisticated targeting. Yet one complaint some buyers have raised recently is that they are worried that the each of the big TV companies will build its own unique systems and processes for data-driven advertising. That level of complexity might hold back the overall market’s potential, these buyers say.

With Audience Studio, will NBCU be accused of going its own way? Mr. Bhatia said that he’d be more than willing to listen if such a broader effort were under way. But, we don’t have the luxury to wait for that solution to emerge,” he said. “We’d be the first people to think through how we might use that to help our clients. But right now we want to establish a leadership position and let our ad clients use any sort of data you could possibly imagine for advertising.”

MY POV: With yet another possible target marketing option in the marketplace, marketers need to take a really close look at the technology their currently have. It may mean that they do a “bake off” and determine, by comparing actual results, what technologies and platforms will really serve their needs to not only target the right audience, but also to increase lead conversion rates. The good thing is marketers have more choices than ever. The bad thing is, marketers have more choices than ever.

The combination of mobile, social, sensor, wearable and cloud technologies has triggered a deluge of data. More than 90 percent of the world’s data has been generated over the last two years. And, with the number of connected devices projected to reach 75 billion by 2020, the volume of data available is expected to grow exponentially. Without making sense of all this data, we just have a ton of nothingness and a lot of talk about possibility. But it’s time for possibility to turn into probability. And that’s what is in store for companies that are looking at the IOT Cloud.

This world of connected devices and digital content presents an enormous opportunity for companies to take advantage of the new data. In a June 2015 report, the McKinsey Global Institute estimates that IoT applications may have a potential economic impact of as much as $11.1 trillion per year by 2025. However, businesses have been unable to capitalize on the vast volume of data from the Internet of Things.

Salesforce IoT Cloud, Powered by Thunder—Connecting to the Internet of Customers IoT Cloud empowers businesses to connect data from the Internet of Things, as well as any digital content, with customer information, giving context to data and making it actionable—all in real-time. Thunder, built on a massively scalable, modern architecture, can “listen” to the connected world, ingesting billions of events a day, from any source. IoT Cloud’s capabilities include:

Listen to the World at IoT Scale: IoT Cloud connects everything to Salesforce. In addition to the Internet of Things, connecting to phones, wearables, windmills and industrial turbines and other devices, IoT Cloud connects data from websites, social interactions and more to Salesforce. By connecting the billions of real-time events and digital content with Salesforce, the IoT Cloud brings customer context to transactional data.

Trigger Actions with Real-time Rules: With IoT Cloud, business users can use intuitive, point- and-click tools to define, modify and set rules and logic for events that can trigger actions across Salesforce. A global fleet management company, for example, can enforce passenger safety standards by setting filters for “hard brakes” or “hard accelerations” and defining rules that trigger in-car sensors to log service cases reporting possible instances of erratic driving. Or, a national retailer holding a holiday sale can set rules based on loyalty program status, inventory or sales performance, triggering retail beacons to send discount offers to in-store shoppers in real-time.

1:1 Proactive Engagement through Salesforce: IoT Cloud seamlessly works across the Salesforce Customer Success Platform to surface insights and trigger real-time 1:1, personalized actions for sales, service, marketing or any other business process. For example, a thermostat provider can parse through billions of events gathered from weather forecasts, sensors and temperature settings to proactively alert customers on how to manage their HVAC usage within their predefined budget. Or, a vehicle assistance service partnering with an auto brand can send personalized offers on behalf of local dealers based on sensor data that tracks fluid levels and mileage.

IoT Cloud connects billions of events from devices, sensors, applications and more from the Internet of Things to Salesforce—enabling companies to unlock insights from the connected world. IoT Cloud is powered by Salesforce Thunder, a massively scalable, real-time event processing engine that enables Salesforce customers to personalize the way they sell, service, market… IoT leaders ARM, Etherios, Informatica, PTC ThingWorx and Xively LogMeln join Salesforce’s ecosystem to accelerate IoT Cloud customer success. Companies including Emerson and Pitney Bowes look to connect with their customers in powerful new ways with IoT Cloud.

Marc Benioff, chairman and chief executive officer, Salesforce said, “Salesforce is turning the Internet of Things into the Internet of Customers. The IoT Cloud will allow businesses to create real-time 1:1, proactive actions for sales, service, marketing or any other business process, delivering a new kind of customer success.”

The IOT Cloud is the beginning of making sense of all the data turn information into actionable insights that really move the needle on a businesses growth, revenue, and bottomline. It’s time technology delivered on the promise of yesterday year and that time is now. To see how it can work, check out this video.

Fresh off the first of the digital disruption tour events, I am reflecting on the wonderful conversation that Ray Wang lead with his keynote speech, really defining this new era of business. If you want to really understand what he’s talking about, you not only must see him speak — he draws such a clear picture of the future, but to really allow what’s happening to infiltrate your department or functional area or your own leadership, his book, Disrupting Digital Business, is very helpful — with examples and details.

For customer experience professionals, that was my roundtable discussion, we talked about not only this new era of business, but the requirement of company’s to change their business models to be able to deliver on the promise of whatever customer experience they are offering. Doesn’t matter if it’s B2B or B2C or B2B2C- customer’s have expectations. Why is it so different today than its ever been? For many of us at the roundtable discussion– we’ve been talking about customer experience, customer service, customer success management for most of our professional lives. It’s not new. And it’s not really a new topic inside of companies.

What is new and what does require something different of organizations is the transparency of how the customer experience affects a business’s customers. In the old days, the customer experience might have been between a contact center agent and a customer. And depending on how empowered that agent was (which generally they were not) that empowerment or lack there of, generated a certain customer experience. It was also dependent on technology as well as processes that were either well defined and implemented or not. If it was a bad experience, that customer would often tell 10-20 people within their circle of influence.

Today, customer loyalty and advocacy is different. Why? Because today the world can see, in an instant, what a brand’s customer experience is and because customers can easily speak to other customers, often going around the brand, brand’s have to walk their talk. And while the Directors of Corporate Communication, PR, the CMO and marketing spend tireless hours and hundreds if not millions or more in budget to create a “brand” — whether that “brand” ends up living up to expectations is dependent on so many things; it now requires we change how we do business so nothing falls through the cracks. It requires collaboration between all functional departments and the back office.

Ultimately, a brand ends up being expressed as the experience a customer has with that brand. And because there are so many people, departments, touch-points — at any point in that customer’s interaction with that brand, the brand may not uphold its promise. And because of the nature of social networks, that “good or bad” experience, can be expressed for millions to see, in a nano-second, often lasting a long time (think of “online posts” like cave paintings – they last millions of years…) The expression of a brand from a customer can be very personal and emotional. And often times the expression from the brand’s side is through content. And the number of people and budget, just for content marketing, has really shifted how we must think about how we do business. Business has changed. Period.

I really want to thank each and every person who participated in the customer experience roundtable. What our roundtable discussion concluded where several things:

1. Good customer experience starts with strategy. It’s not just about implementing the technology. It’s about looking at your business processes from the customer’s point of view and making changes to what does not make sense. It’s about examining the commitment from the senior leadership team to allow for budget so that the people, process and technology required for great customer experiences can be delivered.

2. Good customer experience also requires something new of the internal aspects of a company – culture, leadership, employees, training, attitude… and while most of what I write about is that “external” customer-facing experience, the truth is that – that customer experience can’t be good if the internal capabilities of an organization are not optimized. It is something that is often underestimated and rarely spoken about, but at the end of the day, it’s employees who are driving the customer experience in one shape or form. So it’s my feeling that this part of the conversation can no longer can be ignored. And in some cases, it maybe the first step in generating great, external-facing customer experiences.

The Panel Discussion One of the panels was on the customer experiences created in the financial services area. Financial service companies often think of themselves as limited to change things because of all the regulations they face. When Ray was asked about this he explained, “While there are many regulations, smart companies are looking at those regulations, often written years ago and asking if they make sense today. If they don’t, smart companies and governments are taking the time to question them and transform whatever it takes to make things work better.”

Wipro (who sponsored this SF part of the tour) talked about the ideas behind banking 1:1. Even in a highly regulated and competitive marketplace, banks must examine every possible idea and strategize about the advantages it can use to meet and to exceed customer expectations. This is truly, for all industries, where companies will differentiate themselves from the pack, now and in the future. Banks can’t offer simple and automated banking services. To build loyalty and drive profitability, banks need to offer a non-stop interactive banking environment and to increase their business agility by anticipating customer needs and offer an engaging user experience.

I vowed to keep writing about customer experience and customer service / success management – the ability to use data to understand our customers better to provide better experiences – as well as technology, people and processes. But I also asked that each one of the people in my roundtable take it upon themselves to hold the torch to generate excellent customer experiences. That’s because transforming businesses today, to provide great customer experiences, takes a village; it’s not a one person job. It takes collaboration across functional departments and strong leadership from all of us.

So as you read this, I ask you to also hold the torch for great customer experiences and for what the “transparency and digital disruption” means and requires of each of us – i.e., that what we are really talking about is that we all have to change our business models (or how we do business.) And together, I believe we can transform business. It’s something that has been a long time in coming. It’s here. It’s now. It’s something I want to see in my lifetime. How about you?

Wondering what consumers were interested in this year? Wondering what the top gift was? How many millions or billions of dollars of products were bought and where? How social networks played into the shopping equation? This post provides data on all of these topics and more. Adobe released its 2014 Digital Index Online Shopping data for the holiday season. Between November 1 and November 28, $32 billion have been spent online. That is 14 percent more than in 2013. Thanksgiving Day and Black Friday set new sales records with $1.33 billion and $2.4 billion, respectively.

When people talk about sleeping with their phones, it seems that the trend is continuing as mobile devices continue to play a dominant role. For the first time smartphones nearly doubled their share of total online sales on both days. November 11 (“Singles’ Day”) set a new sales record with $1.29 billion and is expected to surpass Cyber Monday in growth this year. The average order value for sales coming directly from a social network was led by Facebook with $114.45.

Wondering how the data was collected? The findings are based on the analysis of aggregated and anonymous data of more than 350 million visits to 4,500 retail websites. More than $7 out of $10 spent online with the top 500 U.S. retailers were measured by Adobe Marketing Cloud. Measuring this amount of data puts Adobe in a unique position to possibly deliver highly accurate, census-based online sales totals, pricing and product availability trends as well as other retail data.

For those companies that want and need this type of data to provide better and next generation customer experiences, this type of data is really important. Companies need to see where their customers are and where and how they make their purchase decisions. Some of the trends that Adobe was looking at are as follows:

Total Online Spend: Consumers spent$32 billion online so far this season, a 14 percent growth year-over-year (YoY). Both Thanksgiving Day and Black Friday saw double-digit growth in online sales, 25 and 24 percent respectively. The increase in sales was driven by brick-and-click retailers, who saw the biggest jump YoY with nearly 30 percent. Online sales conversions also improved. 3.2 percent of visits resulted in a completed shopping cart, up from 3.14 percent in 2013. The average order value was $149 on Thanksgiving Day, and $142 on Black Friday. The number of people choosing to order online and pickup in-store rose to 45 percent above normal on Thanksgiving Day.

Mobile Trends: Smartphones and tablets continued to drive online sales. 29 percent of sales on Thanksgiving Day came from mobile devices, up from 21 percent in 2013. Mobile devices drove 27 percent of sales on Black Friday, three percent more than last year. The share for smartphones rose to 13 percent and almost doubled compared to seven percent last year. The share for tablets only increased slightly to 16 percent from 14 percent in 2013. iOS users drove four times as much mobile sales revenue as Android users, 79 and 21 percent respectively.

Best Deals: Between Sunday and Monday before Thanksgiving the average online price fell 5.5 percent, 0.5 percent more than forecasted, representing the highest price drop in a single day in 2014. Thanksgiving Day saw the lowest prices online with an average discount of 25.2 percent, 1.2 percent lower than in 2013.

Impact of Social Networks: The average order value (AOV) for sales coming directly from social networks was led by Facebook with $114.45. Pinterest came in second with $93.20, and Twitter drove online sales of $90.74 on average. Pinterest saw the largest YoY increase in AOV, up 16 percent. Facebook (seven percent) and Twitter (five percent) also saw slight increases. Two percent ($74.6 million) of purchases came directly from social media sites, which is flat compared to 2013.

Singles’ Day Surprise: For the first time, Singles’ Day let U.S. retailers start the holiday shopping season earlier this year. Online sales on November 11 set a new record with $1.29 billion, a 16 percent YoY increase, and close to online sales on Thanksgiving with $1.33 Billion. Singles’ Day is expected to grow faster than Cyber Monday and become one of the top five days with the lowest online prices this season.

Top Gifts: Social media buzz continued to be an early indicator for top gifts. 4K TVs saw the biggest jump in social buzz month-over-month (MoM) with social media mentions for Sony and Samsung increasing 350 percent. Fitbit led the wearable device category, which had 100,000 social mentions on Thanksgiving and Black Friday while iPhone 6 continued to lead in the smartphone category.

“Consumer use of larger screen smartphones helped drive significant increases in mobile online sales – enough to set records two days in a row,” said Tamara Gaffney, principal analyst, Adobe Digital Index.

This type of data and its use- meaning not just data but insights that are business actionable- are what will make next generation customer experience rock in the coming years. It will be interesting to see how many companies really begin to use “big data” and analytics in ways that end up helping companies gain and retain their customers.

@drnatalie

VP and Principal Analyst, Covering Marketing, Sales and Service To Deliver Great Customer Experiences

Delta Air Lines’ legacy in-flight point-of-sale system (POS) system could only provide very basic transaction data for items like meals, headphones and duty-free items. Declines in credit card purchases remained undetectable until the flight landed, leading to lost revenue. In addition, the in-flight POS system lacked the ability to communicate in real time with Delta’s CRM system, resulting in a disjointed customer experience.

Learn how Delta Air Lines enhanced customer experience and reduced lost revenue by implementing a mobile, in-flight POS system powered by Microsoft Dynamics and Avanade.

Table of Contents:

The Company

The Challenges

Improving Efficiency and Effectiveness In-Flight for Beverage, Food and Duty-Free Purchase System

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Dr. Natalie is a business strategist and a futurist. She has spent her careers looking about how businesses interact with their customers and their employees and she provides companies with the best way to create environments that foster loyatly, motivation and innovation.